System, method, and computer program for providing notification of a cashback reward from a shopping portal using online screen and email analysis

ABSTRACT

The present disclosure relates to a system, method, and computer program for providing users with notifications of a cashback rewards from a shopping portal using screen and email analysis. A shopping portal system analyzes the content and characteristics of user emails, as well as screens viewed by the user through a client application (e.g., webpages and mobile application screens), to identify probable order-confirmation emails and screens. In response to identifying an order-confirmation email or an order-confirmation screen, the system determines whether a cashback reward should be credited to the user for the order corresponding to the order-confirmation email/screen. In response to an order-confirmation email or screen satisfying the criteria for a cashback reward, the system credits a user account with the cashback reward and notifies the user of the reward.

BACKGROUND OF THE INVENTION 1. Field of the Invention

This invention relates generally to ecommerce systems, and, morespecifically, to a system that provides notifications of cashbackrewards based on email and online screen analysis.

2. Description of the Background Art

Certain shopping portals, such as EBATES, provide users with cashbackrewards in response to users purchasing products online from partnermerchants via the shopping portal. The cashback reward is typically apercentage of a purchase price, wherein the percentage may vary based onthe merchant. To earn a cashback reward, a registered user of theshopping portal connects to a partner merchant's site through theshopping portal. The user may connect through a mobile application forthe shopping portal, a browser with a browser extension for the shoppingportal, or a website for the shopping portal. The partner merchant mayuse cookies to identify purchasers who linked to their site from theshopping portal. Periodically (e.g., weekly, monthly, quarterly), thepartner merchant will send the shopping portal a report with the userswho purchased products from the merchant in shopping sessions initiatedfrom the shopping portal. For each purchase, the report includes thecorresponding purchase amount.

The cashback shopping portals use the reports from partner merchants tocalculate cashback rewards earned by users. Because a merchant reportmay come up to several weeks or more after a purchase, a challenge forsuch shopping portals is that there is delay between when users makespurchases and when users see their cashback rewards in their cashbackaccounts. Typically, the shorter the time between when a user makes thepurchase and is notified of the cashback reward, the more incentivizedthe user is to use the shopping portal. Therefore, there is marketdemand for a solution that enables the shopping portal to “instantly”calculate and notify a cashback reward when a user makes a purchase.

SUMMARY OF THE DISCLOSURE

The present disclosure relates to a system, method, and computer programfor using screen and email analysis to provide users with notificationsof cashback rewards earned on qualifying online purchases. The methodenables a shopping portal that provides cashback rewards to notify usersof earned rewards shortly after users make purchases instead of waitingfor periodic merchant reports. To the user, it appears to be an“instant” cashback reward because the reward appears shortly after thepurchase.

The system analyzes the content and characteristics of user emails toidentify probable order-confirmation emails. The system also analyzesthe content and characteristics of screens viewed by the user through aclient application (e.g., webpages and mobile application screens), toidentify probable order-confirmation screens. Order-confirmation emailsand order-confirmation screens are emails and screens, respectively,that acknowledge an online order. Emails and screens identified asprobably order-confirmation emails and screens are referred to herein as“email captures” and “screen captures,” respectively.

The system parses email captures and screen captures to extract datavalues, including but not limited to date and time stamp, order number,and purchase amount. The extracted data values are stored in associationwith a user identifier and a merchant identifier corresponding to theemail/screen capture.

For each email capture and screen capture, the system determines if theorder corresponding to the capture is an order that qualifies for acashback reward with the shopping portal. This includes determining ifone or more extracted data values (e.g., a promo code) correspond tovalid terms of a reward-qualifying order. For example, the system maydetermine if there is a valid promo code in an email or screen capture(e.g., a promo code associated with the shopping portal). For an emailcapture, determining whether an order qualifies for a cashback rewardalso includes ascertaining if the order described in the email waslikely placed in an online merchant shopping session initiated from theshopping portal. The system makes this determination by comparing datavalues extracted from the email capture to online merchant shoppingrecords for the user.

In response to determining that the email/screen capture corresponds toa reward-qualifying order, the server determines if a cashback rewardhas already been credited to the user for the order based on a previousemail/screen capture. For an email capture, the system determines ifthere is a corresponding screen capture. Likewise, for a screen capture,the system determines if there is a corresponding email capture.

If the system finds a corresponding capture, the system determines if acashback reward was previously credited for the corresponding capture.If so, there is no further cashback reward for the new capture. If theemail/screen capture corresponds to a reward-qualifying order and noprevious cashback reward has been credited to the user for the order,the system calculates the cashback reward. The system credits thecorresponding user account with a cashback reward, and provides anotification to the user of the reward. Examples of the ways in which auser may receive a notification include: a browser notification, amobile application push notification, an email, a text, and updatedaccount information on a website for the shopping portal.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram that illustrates an example systemarchitecture.

FIGS. 2A-2B are flowcharts that illustrate a method, according to oneembodiment, for providing users with notifications of a cashback rewardsusing screen and email analysis.

FIGS. 3A-C are flowcharts that illustrate an example implementation ofthe reward calculation in response to identifying an email as a probableorder-confirmation email.

FIGS. 4A-C are flowcharts that illustrate an example implementation ofthe reward calculation in response to identifying an online screen as aprobable order-confirmation screen.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present disclosure relates to a system, method, and computer programfor using screen and email analysis to provide users with notificationsof cashback rewards earned on online purchases initiated via a shoppingportal. FIG. 1 illustrates an example system architecture forimplementing the methods described herein. A client application 110executes on a client computing device 105, such as a smart phone,laptop, tablet, or desktop computer, and enables the user to accessonline merchant shopping sites 150 via the shopping portal.

The client application 110 may be a general-purpose web browser (e.g.,SAFARI, CHROME, FIREFOX, EXPLORER, etc.) with a browser extension thatenables a user to access a plurality of different (and unrelated)merchant websites via the shopping portal. For example, when a usernavigates to a partner/associated merchant website, a user with thebrowser extension may click on a button displayed by the browserextension to be redirected to the merchant website via the shoppingportal. In redirecting the user, the browser extension adds a cookie tothe merchant webpage that indicates that the web visit initiated fromthe shopping portal. As used herein, the term “browser extension”applies to any software code that executes within the context of a webbrowser and extends the normal functionality of a browser, including,but not limited to browser extensions and browser add-ons.

The client application 110 may also be a mobile application for theshopping portal, via which a user accesses a plurality of different (andunrelated) merchant shopping sites.

The client application 110 includes a screen capture module 120 thatanalyzes online screens rendered to the user in the client application110 in order to identify order-confirmation screens, as described inmore detail below. With respect to a web client with a browser extensionfor the shopping portal, the screen capture module 120 may be part ofthe browser extension.

The system includes a server 130 associated with the shopping portal.The server 130 receives records from client applications 110 of shoppingsessions at merchant sites initiated through the client applications. Arecord of these shopping sessions is maintained in a database 185. Theserver 130 also receives screens identified by screen capture modules120 within users' client applications as being likely order-confirmationscreens. Furthermore, the server 130 includes an email capture module195 that obtains users emails from email servers 190 and analyzes theemails to identify order-confirmation emails from applicable merchants(i.e., merchants for which a cashback reward is eligible). As describedbelow, the server 130 further analyzes the email and screen content andcalculates cashback rewards as appropriate. The other modulesillustrated in FIG. 1 are discussed below with respect to FIGS. 2-4.

For example purposes, the components/modules of FIG. 1 are referenced inthe description of FIGS. 2-4. However, the methods described herein maybe implemented in a system configured differently and are not limited tothe system architecture illustrated in FIG. 1.

FIGS. 2A-B illustrates a method for providing users with notificationsof a cashback rewards from a shopping portal using screen and emailanalysis. As illustrated in steps 205-220, the method includes parallelprocesses for capturing order-confirmation emails and order-confirmationscreens.

Email Order-Confirmation Capture

An email capture module (e.g., email capture module 195 in FIG. 1) on aserver associated with the shopping portal (“the server”) analyzescontent and characteristics of emails from merchants to determinewhether any emails are likely order-confirmation emails (step 205). Theemail capture module may obtain and assess the emails (e.g., messagecontent and metadata) from an email server by authenticating andsecurely connecting to the email server.

In one embodiment, to ascertain whether an email is a likelyorder-confirmation email from an applicable merchant (i.e., a merchantfor which a cashback reward may be eligible), the email capture modulefirst determines whether the email was sent by an applicable merchant.As a merchant may use several email addresses, mapping logic may be usedto determine whether the email address is associated with an applicablemerchant (e.g., the email address is compared to merchant emailaddresses in a look-up table). In alternate embodiment, machine learningmay be used to determine whether the email is from a relevant/applicablemerchant.

If the email was sent by an applicable merchant, the email capturemodule then determines whether the email is an order-confirmation email.In one embodiment, the module determines whether the email includes aminimum number of phrases and/or characteristics associated with amerchant's order-confirmation email. For example, the email capturemodule may compare the email to merchant order-confirmation emailtemplates. The email capture module may use regular expressions to dosuch comparison. In another alternate embodiment, machine learning isused to determine if the email is an order-confirmation email.

The email capture module may consider the current date in relation tothe email date and/or order date. It may disregard emails or orders thatare n many days before the current date.

In response to determining that an email is likely a validorder-confirmation email with a threshold degree of confidence (e.g.,90% confident), the email monitoring module stores the email in adatabase (e.g., database 140) (step 210) for further processing by theserver.

Online Screen Order-Confirmation Capture

A screen capture module within each client application (e.g., screencapture module 120) analyzes content and characteristics of screensrendered within the client application to determine whether any of thescreens are likely order-confirmation screens from applicable merchants(step 215). The screen capture module analyzes the screens insubstantially real time as the screen is displayed within the clientapplication.

In one embodiment, the screen capture module first determines whether ascreen rendered in a client application is from an applicable merchantbased on the domain of the screen. If the domain corresponds to anapplicable merchant, the screen capture module then compares thecontent/characteristics of the rendered screen to phrases and/orcharacteristics associated with the merchant's order-confirmationscreen. The characteristics of a screen may include the URL of thescreen. The screen capture module may use regular expressions to do thecomparison. In an alternate embodiment, machine learning is used todetermine if the screen is an order-confirmation screen. In response toconcluding with a threshold degree of confidence (e.g., 90% confident)that a screen is likely an order-confirmation screen, the clientapplication sends screen information to the server (step 220), whichstores the screen data in database 140 for further processing by theserver.

Cashback-Reward Calculation

As used herein, the terms “email capture” and “screen capture” refer toemails and online screens identified in steps 205-220 to be likelyorder-confirmation emails and order-confirmation screens, respectively,from applicable merchants.

The shopping portal server (e.g., server 130) further parses emailcaptures and screen captures to extract data values, including date andtime stamp, order number, and purchase amount (step 225). The extracteddata values are stored in association with a user identifier and amerchant identifier corresponding to the email/screen capture. If theserver is unable to successfully extract required data values from anemail or screen capture, the server disregards the capture for thepurpose of calculating a cashback reward. In the system of FIG. 1,parser module 175 performs step 225 and then stores the extracted datavalues in database 140. In certain embodiments, this parsing could bedone by the capture modules.

For each email capture and screen capture, the server determines if theorder corresponding to the capture is an order that qualifies for acashback reward with the shopping portal (step 230). Specifically, foran email capture, the server determines if the order described in theemail was likely placed in an online merchant shopping session initiatedfrom the shopping portal. The server separately maintains a record ofall online shopping sessions initiated through the shopping portal(e.g., database 185), and, in one embodiment, the server determines ifthe user used the shopping portal to initiate an online shopping sessionat the same merchant within a certain window of time prior to either theorder date and time set forth in the email (if available) or the dateand time of the email transmission. Other factors may also be used incomparing email captures and online shopping sessions, such as comparingpromotional codes, payment method, and product descriptions.

In response to finding an online shopping session for the user thatcorresponds to the email capture (e.g., time, user, and merchantsubstantially match), the server determines if the order terms are valid(e.g., a valid promotional code). If so, the server concludes that theemail capture corresponds to an order that qualifies for a cashbackreward with the shopping portal (a “reward-qualifying order”).

For a screen capture, the server performs step 230 by determining if oneor more extracted data values correspond to valid terms of areward-qualifying order. For example, the server may determine if therea valid promotional code in the screen capture (e.g., a promo codeassociated with the shopping portal). Validation may also depend on thetype of product purchased, the method of payment, and time of onlinesession. If the applicable data values from the screen capture arevalid, the server concludes that the screen capture corresponds to areward-qualifying order.

In response to determining that the email/screen capture corresponds toa reward-qualifying order, the server determines if a cashback rewardhas already been credited to the user for the order based on a previousemail/screen capture (step 235). For an email capture, the serverdetermines if there is a corresponding screen capture in database 140.Likewise, for a screen capture, the server determines if there is acorresponding email capture in database 140. In either case, the serverconcludes that there is a corresponding capture if a number of factorsmatch or substantially match across the two captures, such as user,merchant, purchase amount, order number, product name, and date/time.“Fuzzy logic” may be used to perform the matching operations.

If the server finds a corresponding capture, the server determines if acashback reward was previously credited to the user for thecorresponding capture. If so, there is no further cashback reward forthe new capture. In certain embodiments, the server may execute rules todetermine if the cashback reward should be updated based on informationin the new capture.

If the email/screen capture corresponds to a reward-qualifying order andno previous cashback reward has been credited to the user for the order,the server calculates a cashback reward (step 240). In one embodiment,the reward is calculated based on cashback rules for the applicablemerchant and the purchase amount extracted from the new email/screencapture. The server credits the user account with the cashback reward,and provide a notification to the user of the reward (steps 245, 250).The notification may be in the form of one or more of the following: abrowser notification, a mobile application push notification, an email,a text, or update account information on a website for the shoppingportal. In one embodiment, a notification based on a screen capture issent within seconds or minutes (e.g., 30-120 seconds) of the orderconfirmation screen being displayed with the client application, and anotification based on email capture is sent within minutes of the emailbeing transmitted (e.g., 2-3 minutes). The notification may include thespecific reward amount or may be a general notice that a reward has beenearned. The notification may or may not include specific order details,such as the order number, date, merchant name, purchase amount, etc. Thenotification also may indicate that the reward is pending, as it may besubject to subsequent confirmation based on merchant reports.

In the system illustrated in FIG. 1, reward calculation module 165performs steps 225-250. Email and screen capture data is stored indatabase 140, online shopping session records are stored in database185, and user cashback reward balances are stored in database 180.

FIGS. 3A-C illustrates an example implementation of the above-describedreward calculation in response to the server identifying an email as aprobable order-confirmation email (i.e., in response to a new emailcapture). As described above, in response to receiving a new emailcapture, the server parses the email content and metadata to extractdata values, including purchase amount, an order number, an order dateand time (if available), an email transmission date and time, and asource merchant (i.e., the merchant that sent the email) (steps 305,310). The server then determines whether the user had a correspondingonline shopping session (using the shopping portal) at the same merchantduring a select time period (e.g., 2 hours) prior to either the orderbeing completed (if an order time was extracted from the email) or theemail being sent (step 320). The server access online shopping sessionrecords to perform this determination (e.g., records in database 185).As stated above, other factors (i.e., other extracted data values) alsomay be used in determining whether there is a corresponding onlinesession.

In response to step 320 evaluating to true, the server determines if theextracted order terms in the email are valid with respect to earning areward (step 330). If so, the server concludes that the emailcorresponds to a reward-qualifying order (step 335). If either step 320or 330 evaluates to false, the server does not proceed with calculatinga cashback reward based on the email (step 340).

In response to determining that the email corresponding to areward-qualifying order, the server determines whether there is apreviously-captured online screen that corresponds to the same order asthe email (step 350). If the server finds a corresponding online screencapture, the server determines if a cashback reward was previouslycredited to the user for the order (step 360). If so, the server doesnot calculate an additional cashback reward (except that in certainembodiments, the server may execute rules to determine if the emailcapture results in an update to the cashback reward) (step 370).

If there is no corresponding screen capture or no cashback reward wascredited for a corresponding screen capture, the server calculates acashback reward for the user based on a cashback percentage offered bythe applicable merchant and the purchase amount in the email capture(step 380). The server credits a reward account for the user with thecashback reward (step 385), and the server provide a substantiallyreal-time notification to the user of the cashback reward (step 390).

FIGS. 4A-C illustrates an example implementation of the above-describedreward calculation in response to the server identifying an onlinescreen as a probable order-confirmation screen (i.e., in response to anew screen capture). As described above, in response to receiving a newscreen capture, the server parses the screen content to extract datavalues, including purchase amount, an order number, a screen capturetime and date and/or an order date and time, and a source merchant(steps 405, 410).

The server then determines whether one or more data values extractedfrom the screen correspond to a valid shopping session with the shoppingportal (e.g., does the promotional code correspond to the shoppingportal?) (step 420). In response to step 420 evaluation to true, theserver concludes that the screen corresponds to a reward-qualifyingorder (step 430). Otherwise, the server does not proceed withcalculating a cashback reward based on the screen capture (step 440).

In response to determining that the screen corresponding to areward-qualifying order, the server determines whether there is apreviously-captured email that corresponds to the same order as thescreen capture (step 450). If the server finds a corresponding emailcapture, the server determines if a cashback reward was previouslycredited to the user for the order (step 460). If so, the server doesnot calculate an additional cashback reward (except that in certainembodiments, the server may execute rules to determine if the screencapture results in an update to the cashback reward) (step 470).

If there is no corresponding email capture or no cashback reward wascredited for a corresponding screen capture, the server calculates acashback reward for the user based on a cashback percentage offered bythe applicable merchant and the purchase amount in the screen capture(step 480). The server credits a reward account for the user with thecashback reward (step 485), and the server provide a substantiallyreal-time notification to the user of the cashback reward (step 490).

In certain embodiments, the system identifies and parsesshipping-notification emails (i.e., an email confirming that a productordered online has shipped) in the same manner that order-confirmationemails are identified and parsed. Data extracted fromshipping-notification emails may be used to notify users of pending orearned rewards in the same manner as described with respect toorder-confirmation emails.

The system and methods described herein can be applied to rewards otherthan cashback rewards and are not necessarily limited to cashbackrewards. For example, if the shopping portal enables users to earnmerchant credits on purchases, the methods could be used to notify usersof merchant credits earned based on email and screen analysis.

In certain embodiments where machine learning is used to determinewhether an email or screen is an order-confirmation email/screen, thesystem creates a statistical model (e.g., a Bayesian model) that mapsscreen/email characteristics and content elements to a probability ofbeing an order-confirmation screen/email. The model may be trained withtraining data that includes screens and emails labeled as to whetherthey are order-confirmation screens/emails. To subsequently use themodel, the system creates an input vector from multiplecharacteristics/content extracted from a screen/email, and applies theinput vector to the statistical model to obtain a probability that theemail/screen is an order-confirmation page. In response to theprobability exceeding a threshold (e.g., 0.9), the system concludes thewebpage is an order-confirmation screen/email.

The methods described herein are embodied in software and performed by acomputer system (comprising one or more computing devices) executing thesoftware. A person skilled in the art would understand that a computersystem has one or more memory units, disks, or other physical,computer-readable storage media for storing software instructions, aswell as one or more processors for executing the software instructions.

As will be understood by those familiar with the art, the invention maybe embodied in other specific forms without departing from the spirit oressential characteristics thereof. Accordingly, the above disclosure isintended to be illustrative, but not limiting, of the scope of theinvention.

The invention claimed is:
 1. A method, performed by a computer system, for providing a user with a notification of a cashback reward using screen and email content analysis, wherein the cashback reward is based on a purchase originating from a shopping portal that offers cashback rewards, the method comprising: maintaining a record of online shopping sessions in which the user used the shopping portal, including recording a merchant and time associated with each online shopping session; analyzing content and characteristics of emails received by the user from merchants to determine whether any emails are probable order-confirmation emails; analyzing content and characteristics of online screens rendered to the user via one or more client applications to determine, in substantially real time, whether any of the screens are probable order-confirmation screens; identifying an email as a probable order-confirmation email; parsing the email content and metadata to extract a plurality of data values, including a purchase amount, an order number, an order date and time if available, and a source merchant; determining if the email corresponds to a qualifying order for a cashback reward by determining whether the user used the shopping portal in an online session for the source merchant during a select time window prior to the order date and time or the email being sent; in response to determining that an email corresponds to a qualifying order, determining if a cashback reward has already been credited to the user for the order, wherein such determination comprises: determining if the system previously captured an online screen that corresponds to a same order as the email; and in response to identifying an online screen previously captured by the system for the same order, determining if a cashback reward was previously credited to the user based on the online screen; in response to determining that the system has not previously provided a cashback reward to the user for the order, calculating a cashback reward; crediting a reward account for the user with the cashback reward; and providing a substantially real time notification to the user of the cashback reward.
 2. The method of claim 1, further comprising: identifying a screen rendered to the user as a probable order-confirmation screen; parsing the screen content to extract a plurality of data values; determining if the screen corresponds to a qualifying order for a cashback reward by determining whether data values extracted from the screen content correspond to a valid session at the shopping portal; in response to determining that the screen corresponds to a qualifying order, determining if a cashback reward has already been credited to the user for the order, wherein such determination comprises: determining if the system previously captured an email that corresponds to a same order as the screen; and in response to identifying an email previously captured by the system for the same order, determining if a cashback reward was previously provided to the user based on the email; in response to determining that the system has not previously provided a cashback reward to the user for the order, calculating a cashback reward; crediting a reward account for the user with the cashback reward; and providing a substantially real time notification to the user of the cashback reward.
 3. The method of claim 1, wherein an email is identified as a probable order-confirmation email in response to the email including a minimum number of same phrases and/or characteristics as an order-confirmation email from the merchant.
 4. The method of claim 1, wherein a screen is identified as a probable order-confirmation screen in response to the screen including a minimum number of same phrases and/or characteristics as an order-confirmation screen for the merchant.
 5. The method of claim 1, wherein a screen is identified as a probable order-confirmation screen in response to the screen content satisfying a regular expression of an order-confirmation screen for the merchant.
 6. The method of claim 1, wherein the notification is sent using one or more of the following: browser notification, mobile application push notification, device push notification, user account update on a website, or email.
 7. The method of claim 1, wherein determining if the email corresponds to a qualifying order for a cashback reward includes determining whether the email was transmitted by a merchant from which a cashback reward can be earned.
 8. A computer system for providing a user with a notification of a cashback reward using screen and email content analysis, wherein the cashback reward is based on a purchase originating from a shopping portal that offers cashback rewards, the system comprising: one or more processors; one or more memory units coupled to the one or more processors, wherein the one or more memory units store instructions that, when executed by the one or more processors, cause the system to perform operations of: maintaining a record of online shopping sessions in which the user used the shopping portal, including recording a merchant and time associated with each online shopping session; analyzing content and characteristics of emails received by the user from merchants to determine whether any emails are probable order-confirmation emails; analyzing content and characteristics of online screens rendered to the user via one or more client applications to determine, in substantially real time, whether any of the screens are probable order-confirmation screens; identifying an email as a probable order-confirmation email; parsing the email content and metadata to extract a plurality of data values, including a purchase amount, an order number, an order date and time if available, and a source merchant; determining if the email corresponds to a qualifying order for a cashback reward by determining whether the user used the shopping portal in an online session for the source merchant during a select time window prior to the order date and time or the email being sent; in response to determining that an email corresponds to a qualifying order, determining if a cashback reward has already been credited to the user for the order, wherein such determination comprises: determining if the system previously captured an online screen that corresponds to a same order as the email; and in response to identifying an online screen previously captured by the system for the same order, determining if a cashback reward was previously credited to the user based on the online screen; in response to determining that the system has not previously provided a cashback reward to the user for the order, calculating a cashback reward; crediting a reward account for the user with the cashback reward; and providing a substantially real time notification to the user of the cashback reward.
 9. The system of claim 8, further comprising: identifying a screen rendered to the user as a probable order-confirmation screen; parsing the screen content to extract a plurality of data values; determining if the screen corresponds to a qualifying order for a cashback reward by determining whether data values extracted from the screen content correspond to a valid session at the shopping portal; in response to determining that the screen corresponds to a qualifying order, determining if a cashback reward has already been credited to the user for the order, wherein such determination comprises: determining if the system previously captured an email that corresponds to a same order as the screen; and in response to identifying an email previously captured by the system for the same order, determining if a cashback reward was previously provided to the user based on the email; in response to determining that the system has not previously provided a cashback reward to the user for the order, calculating a cashback reward; crediting a reward account for the user with the cashback reward; and providing a substantially real time notification to the user of the cashback reward.
 10. The system of claim 8, wherein an email is identified as a probable order-confirmation email in response to the email including a minimum number of same phrases and/or characteristics as an order-confirmation email from the merchant.
 11. The system of claim 8, wherein a screen is identified as a probable order-confirmation screen in response to the screen including a minimum number of same phrases and/or characteristics as an order-confirmation screen for the merchant.
 12. The system of claim 8, wherein a screen is identified as a probable order-confirmation screen in response to the screen content satisfying a regular expression of an order-confirmation screen for the merchant.
 13. The system of claim 8, wherein the notification is sent using one or more of the following: browser notification, mobile application push notification, device push notification, user account update on a website, or email.
 14. The system of claim 8, wherein determining if the email corresponds to a qualifying order for a cashback reward includes determining whether the email was transmitted by a merchant from which a cashback reward can be earned.
 15. A non-transitory computer-readable medium comprising a computer program that, when executed by a computer system, enables the computer system to perform a method for providing a user with a notification of a cashback reward using screen and email content analysis, wherein the cashback reward is based on a purchase originating from a shopping portal that offers cashback rewards, the method comprising: maintaining a record of online shopping sessions in which the user used the shopping portal, including recording a merchant and time associated with each online shopping session; analyzing content and characteristics of emails received by the user from merchants to determine whether any emails are probable order-confirmation emails; analyzing content and characteristics of online screens rendered to the user via one or more client applications to determine, in substantially real time, whether any of the screens are probable order-confirmation screens; identifying an email as a probable order-confirmation email; parsing the email content and metadata to extract a plurality of data values, including a purchase amount, an order number, an order date and time if available, and a source merchant; determining if the email corresponds to a qualifying order for a cashback reward by determining whether the user used the shopping portal in an online session for the source merchant during a select time window prior to the order date and time or the email being sent; in response to determining that an email corresponds to a qualifying order, determining if a cashback reward has already been credited to the user for the order, wherein such determination comprises: determining if the system previously captured an online screen that corresponds to a same order as the email; and in response to identifying an online screen previously captured by the system for the same order, determining if a cashback reward was previously credited to the user based on the online screen; in response to determining that the system has not previously provided a cashback reward to the user for the order, calculating a cashback reward; crediting a reward account for the user with the cashback reward; and providing a substantially real time notification to the user of the cashback reward.
 16. The non-transitory computer-readable medium of claim 15, further comprising: identifying a screen rendered to the user as a probable order-confirmation screen; parsing the screen content to extract a plurality of data values; determining if the screen corresponds to a qualifying order for a cashback reward by determining whether data values extracted from the screen content correspond to a valid session at the shopping portal; in response to determining that the screen corresponds to a qualifying order, determining if a cashback reward has already been credited to the user for the order, wherein such determination comprises: determining if the system previously captured an email that corresponds to a same order as the screen; and in response to identifying an email previously captured by the system for the same order, determining if a cashback reward was previously provided to the user based on the email; in response to determining that the system has not previously provided a cashback reward to the user for the order, calculating a cashback reward; crediting a reward account for the user with the cashback reward; and providing a substantially real time notification to the user of the cashback reward.
 17. The non-transitory computer-readable medium of claim 15, wherein an email is identified as a probable order-confirmation email in response to the email including a minimum number of same phrases and/or characteristics as an order-confirmation email from the merchant.
 18. The non-transitory computer-readable medium of claim 15, wherein a screen is identified as a probable order-confirmation screen in response to the screen including a minimum number of same phrases and/or characteristics as an order-confirmation screen for the merchant.
 19. The non-transitory computer-readable medium of claim 15, wherein a screen is identified as a probable order-confirmation screen in response to the screen content satisfying a regular expression of an order-confirmation screen for the merchant.
 20. The non-transitory computer-readable medium of claim 15, wherein the notification is sent using one or more of the following: browser notification, mobile application push notification, device push notification, user account update on a website, or email.
 21. The non-transitory computer-readable medium of claim 15, wherein determining if the email corresponds to a qualifying order for a cashback reward includes determining whether the email was transmitted by a merchant from which a cashback reward can be earned. 